Complex projects such as the planning and production of large commercial or military aircraft require the scheduling and coordination of a plurality of resources. The resources to be coordinated may include materials, component parts, personnel, machinery and factory floor space, in addition to other resources. Integration and coordination are particularly important in complex projects since higher-order effects and interactions can adversely affect the cost of the project, the time required for completion of the project, and the risk of failure to deliver the required content. In addition, other variables of importance such as the overall efficiency of the project need to be modeled and measured.
A typical planning scenario may involve several functional roles. Subject matter experts (SMEs) speak for those resources that will be needed to provide deliverables in the plan. Resource managers (RMs) are responsible for coordinating and managing a set of resources. And general managers (GMs) or project managers (PMs) are responsible for achieving objectives by creating, committing resources, and managing plans. At the simpler end of the planning spectrum, all of these roles may be filled by the same person (e.g., “What am I going to make for dinner tonight?”). At the complex end of the planning spectrum, the roles may be filed by many individuals in many different organizational configurations. These relationships may change over a prolonged period of time and may involve contractual obligations and regulatory compliance at several levels.
A business case for a project may provide a framework for the planning activity, and it may include a time frame or required completion/delivery target, a budget for operating expense and acquisition of resources, and assumptions about the availability of constrained resources. For complicated or complex scenarios in highly-competitive environments, and where resources are commonly committed to multiple projects and or activities, conflicts between GMs, PMs, RMs and SMEs may be generated as a result of using traditional, schedule-based planning methods. The resulting representation of the plan is typically infeasible after GMs mandate that PMs create the plan within the business case, and GMs mandate that RMs and SMEs commit to the resulting schedule. Subsequently, the infeasible plan is typically managed by GMs insisting that PMs, RMs, and SMEs meet plan milestones without exceeding cost limits. At some point, reality diverges from the flawed plan in a way that can no longer be ignored, and the plan is reworked. Often, unplanned rework is required to correct problems that were created by the illusion of staying on schedule and under budget. These additional activities are usually at the high-cost end of a development process and may compromise or destroy the value of development programs.
The source of these poor results lies in the way activities are considered and put into a plan based on schedule and budget constraints. SMEs and RMs want to ensure that there will be enough resources (including budget) and enough time so that they can meet their commitments. So schedule durations from start-to-finish are considered as a basis for planning the use of resources.
Although existing process planning methods are useful, they nevertheless exhibit several drawbacks, at least in part due to their reliance on unsupportable schedule-based assumptions. Erroneous models that are used for planning and management produce erroneous decisions that are harmful to the purpose of an organization of resources.
Existing methods of process planning rely on discrete schedule estimates and task precedence relationships rather than the data-driven relationships in the network of deliverables. As such, they devolve into a schedule-based (as opposed to process-based) planning approach. Existing methods are also incapable of supporting the data-driven distinction between concurrent and serial activities. Conventional project management concepts require finish-to-start, finish-to-finish or start-to-start relationships between tasks. These relationships may be modified by applying a lead time to the relationships to account for overlapping (parallel) activity. But this approach relies on assumptions about schedule durations and lead time estimates that ignore the actual, data-driven relationships that govern parallel versus serial activity in a cross-functional environment.
It may therefore be desirable to have an apparatus and method that addresses these drawbacks, and improves upon existing practices.